Performance Evaluation of a QoS Adaptation Framework for Mobile Networks Vasos Vassiliou1 Computer Science Department University of Cyprus 1678-Nicosia, Cyprus
[email protected] Abstract: This paper introduces a framework for the adaptation of QoS in a wireless mobile environment (mobQoS). A main feature of this framework is the ability to cope with inconsistencies created from mobility events (e.g. handoffs) in an end-to-end fashion. Adaptation in this framework is separated into (a) application and (b) network QoS adaptation. We define specific procedures for Mob-QoS changes (upgade and degrade) to better control the amount of QoS signalling and the required update completion time. We demonstrate the advantages of the proposed QoS adaptation framework through simulations.
1. Introduction Next generation wireless networks are expected to be the culmination of all the efforts aimed to create a single type of network architecture and a single suite of services for future communications. Most of the additional requirements in next generation wireless networks are created by the demand for seamless roaming among different systems and worldwide access to the Internet. Additional requirements are also placed on networks because user expectations are increasing to more sophisticated services like multimedia, (image and video) content, and professional services typically related to broadband wired systems. One of the methods traditionally used for providing hard guarantees in wired networks is the use of packet switching technologies like ATM and MPLS. Both technologies differ from other networking technologies in their ability to allow users to specify Quality of Service (QoS) requirements. Integrated Services, even though they are build upon IP-based packet forwarding networks, they still have the mechanisms to provide hard guarantees by reserving related resources throughout the routing path. Providing QoS guarantees in wireless mobile networks is agreeably difficult. Doing so by using techniques borrowed from packet switched networks, is still not a straightforward solution [1] [2] [3]. Impairments are introduced in mobile wireless networks not only by the propagation characteristics of the signal, but also by mobility events. This can cause the QoS levels supported by a base station to vary over time with a direct consequence on the capacity of the cell and the offered quality to existing users [4]. If the setup of a virtual circuit, switched path, or flow is based on strict QoS guarantees, then new paths may not be able to be established when QoS cannot be fulfilled, thus ongoing calls will be forced 1 This work has been partly supported by the European Union under the projects E-NEXT FP6-506869, NEXWAY FP5-37944, and BBONE FP6-507607
to terminate on new calls be rejected during call admission. If there is an associated service level agreement for the dropped (or blocked calls) the operator/provider will certainly be in violation. On the other hand, if a path or call setup is not governed by strict guarantees, but there is some flexibility on the part of the mobile application, then calls will continue to receive service, albeit different (and probably lower). The reseach issue is then how to control application flexibility and QoS changes both at the network ends and the network core. It is the aim of this paper to address these issues and to propose a mobile QoS framework based on application and network adaptation strategies for mobile networks. This paper is organized as follows. Section 2 describes the Mob-QoS framework in detail, explaining what is network and application adaptation and the need for Mob-QoS re-evaluation and end-to-end QoS update as a result of mobile handoffs. Section 3 evaluates the performance of the proposed QoS adaptation strategies via simulation and Section 4 provides some concluding remarks.
2. Mobile QoS Adaptation Framework Following the research of end-to-end QoS provisioning for multimedia wireless networks, we propose a more comprehensive mobile QoS framework for IPbased wireless networks using path or resource reservations (e.q. MPLS or RSVP. The framework is illustrated in Figure 1. The framework distinquishes adaptation in two modes, namely: application and network QoS adaptation. The former includes the methods for adapting the application to changes in the available QoS, while the latter includes the methods used by the network to adapt to changes in re-evaluated QoS requirements. Network adaptation includes the processes of QoS upgrade, degradation and satisfaction. Two concepts are explored further in this work: (a) the use of ‘granted Mob-QoS’ as reference during handoffs and (b) the use of bandwidthchange hysteresis values to control the frequency of QoS adaptation events. A significant proposal is also the use of ’minor’ update process to prevent excessive end-toend QoS update signaling traffic as opposed to a ’major’ update. These issues will be explored in detail in subsequent sections.
2.1.
Application QoS Adaptation
In our proposal we apply the windowing strategy on bandwidth and delay such that applications will specify the minimum operable QoS and the desired QoS. The
Mobile QoS Adaptation
Application QoS Adaptation
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Mob-QoS Re-evaluation
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Mob-QoS Update Minor end-to-end Update
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Figure 1: The Components of the Mobile QoS Adaptation Framework.
former is the minimum bound on bandwidth and endto-end delay requirements before the application fails to work or fails to present useful video/audio/data services to the user. The latter is the upper bound where the application would most desire to operate and agree to pay for. Available QoS is a term used to quantify the current QoS state that can be allocated to the user. Although the available QoS can vary widely, the granted QoS must be within the limits set by the minimum and maximum QoS. With this concept of QoS window, variations in QoS can be accommodated via adaptation, as long as that falls within the upper and lower bounds. Bandwidth adaptation applies to video, audio and data streams. A degradation on bandwidth requirement may require the invocation of a low bit rate video coding technique. Similarly, this can be applied to audio. Obviously, the user-perceived video and audio quality is degraded but the user is not completely denied of service immediately. For data applications (such as FTP, TELNET, etc.,) a drop in throughput does not really matter since the application waits and continues to run until the data transfer is completed or it times-out due to very long delay during packet transit. With the use of a bandwidth window the applications are free to adapt to changes in either the last hop wireless link or the new path towards a mobile node (MN) after a mobility event. It has been shown widely in the literature that applications (such as video) can scale down their QoS requirements without being forced to terminate. The reduction could refer to a different frame rate, picture resolution size, color depth, etc. [5] [6]. In addition, it has been shown that hierarchical encoding and variable compression techniques can also support bandwidth adaptation [7]. Adaptation to delay for multimedia applications is also possible provided that the delay values are within certain limits [7]. Variations of delay due to a longer resultant path after handoffs can be resolved by the use of correctly-sized ‘play-out buffers’ provided that the variation is small enough for a practical buffer size.
2.2.
Network QoS Adaptation
As described at the beginning of the section and shown in Figure 1, network adaptation includes the processes of QoS upgrade, degradation and satisfaction. These are defined as part of the Mob-QoS re-evaluation operation. The second operation in network adaptation is Mob-QoS end-to-end update. The first set of actions can be used whenever a MN migrates across wireless cells having different available Mob-QoS. After such an event, the decision of upgrading, degrading, or maintaining an existing connection QoS needs to be made. In conjunction, a Mob-QoS end-to-end update process is necessary to resolve any QoS inconsistencies that may exist between the wired and wireless links after a handoff. 2.2.1.
Satisfying Mobile QoS
If, after a handoff the new BS is capable of satisfying the QoS required at the wireless last hop including the effects of the handoff process requirements, and the newly selected path can fulfill the QoS requirements expected from the fixed portion of the route (again, including the effects of the handoff) the re-evaluation process is completed and no adaptation takes place. Otherwise, other procedures take place as shown in Figure 2. 2.2.2.
Degrading Mobile QoS
During handoffs, situations can arise when the existing Mob-QoS cannot be fulfilled. To avoid forced termination of an existing connection, the desired Mob-QoS requirements are degraded to enable a successful handoff. This operation lowers the probability of handoff blocking. 2.2.3.
Upgrading Mobile QoS
If after a successful handoff there are available resources in the new path that can be used by the application the upgrade procedure claims these resources. It should be noted that upgrades are not always needed if they are uncontrollable. In the proposed framework bandwidth upgrade hysteresis is used as a damping/limiting factor.
Inter/Intra Handover Completed
Handoff results in Mob-QoS Degrade.
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Handoff results in Mob-QoS Upgrade.
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Figure 2: End-to-End Mob-QoS Degrade and Upgrade Procedures. 2.2.4.
Mob-QoS End-to-End Update
Once a Mob-QoS upgrade or degradation has occurred, there may exist QoS inconsistencies between the wired and wireless links. Mob-QoS end-to-end update occurs after a handoff process is completed. Its purpose is to ensure that QoS changes are made known to the concerned entities, such as base stations, mobile hosts, routers and/or sources. There are three important issues to be examined with relation to updates: • When should the update process take place with relation to the handoff process? • Should we update on every hadndoff? • Who initiates the update process? For the first question, while the approach undertaken in [8] initiates Mob-QoS update within the handoff protocol, it is proposed here that this function is to be “moved out” of the handoff protocol. The rationale behind this move is that the inclusion of a Mob-QoS update mechanism within the handoff protocol will undoubtedly increase the overall handoff time. By separating the QoS update operation from the handoff protocol functions, the overall handoff time is therefore not affected. This is important since the time to perform a handoff is usually critical and it affects the amount of jitter and packet loss introduced into the traffic stream during handoffs. Regarding the frequency of updates we consider that if a Mob-QoS update process is to occur for every mobile handoff, then the resulting signaling traffic can be substantial. Hence, instead of performing a complete endto-end Mob-QoS update, a different strategy is proposed below based on the type of handoff. Finally, although Mob-QoS adaptation can be invoked by the new BS, we have adopted the MN-initiated approach for reasons that will be apparent later. During cases when the new BS ascertains that a Mob-QoS adaptation is necessary, it will send an update signal to the MN. Depending on the nature of the handoff (within the same domain or cluster, i.e. intra-domain handoff or between different domains or clusters i.e. inter-domain
handoff,) the node invokes the appropriate Mob-QoS update procedures. • (A) Minor Mob-QoS Update Strategy During a minor end-to-end Mob-QoS update only the local and remote hosts (mobile or fixed) are informed about the change in Mob-QoS so that the appropriate action can be taken by the application. In the case of a degradation update, the resources reserved over the existing wired links remain unchanged but the new wireless link will have a degraded Mob-QoS. Minor Mob-QoS updates will be more commonly used during intra-domain handoffs. Therefore, the ends of the path will operate using the updated, usually lower, values while the core of the network will be employing more BW than actually needed. This is obviously not very efficient, but it is a fast and basic procedure. The inefficiency of this strategy is reduced by the fact that it is possible to regain the wasted bandwidth by employing a minor Mob-QoS upgrade process at a subsequent intra-domain handoff. • (B) Major Mob-QoS Update Strategy During inter-domain handoffs, the domain default gateway may no longer be a common point between the old and the new paths. Hence, after an interdomain handoff, the new partial path may have different Mob-QoS than the existing path. Usually, after inter-domain handoffs most of the resulting path is new, therefore, a major end-to-end Mob-QoS update process is initiated. In a major update, we inform about the change not only the remote mobile or fixed host, but also all the nodes and BSs related to the new path. The network is now participating in the adaptation as well. Hence, this strategy requires adaptation by all nodes in the path, plus the application at both ends. 2.2.5.
Granted Mob-QoS
Usually the QoS requirements associated with a MN are those the user or the application specifies at call setup, prior to call admission. As soon as the MN is admitted,
Call Types Mobile Call1 Mobile Call2 Mobile Call3 Fixed Call1 Fixed Call2 Fixed Call3
BWmax (Kbps) 256 3000 5000 2000 34000 1000
BWmin (Kbps) 256 1000 1000 1000 2000 100
BW 4 (Kbps) 0 500 1000 250 8000 225
Ave. Interarrival Time 1 2 1 5 10 5
Ave. Call Holding 5 10 2 5 10 1
Table 1: Call types associated with fixed and mobile calls.
3.
3.2.
Simulation Results
The performance parameters of interest are: (a) QoS upgrade probability, (b) QoS degradation probability, (c) QoS fulfillment probability, (d) call blocking probability, and (e) call dropping probability. 3.2.1.
Call Blocking Probability
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some researchers use the QoS granted after the mobile call setup to be the reference point for any new actions with the MN. In this paper, we adopt and extend this concept. When a BS has to decide whether or not to admit a MN after a handoff it uses the “previously-granted” QoS. When the condition of satisfying the “previouslygranted” QoS cannot be met (i.e., Mob-QoS has to be further degraded), a Mob-QoS degradation update will have to be initiated. If the available QoS in the new wireless cell is greater than the “previously-granted” QoS, the desired QoS level will be used as a reference for upgrade. Hence, during a handoff, the triplet {upper, lower, and “previously-granted” QoS } information will be passed to the new BS via the MN or from the old BS. In effect, as a MN hands off from one wireless cell to another, the “previously-granted” Mob-QoS for the mobile also also moves to the new BS. The use of this concept reduces the effort needed by the network to re-update (degrade or upgrade) an already updated call.
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Performance Evaluation of QoS Adaptation Strategy
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The benefits realized by the employment of the scheme described in the previous section are investigated in this section with the use of a discrete-event simulator. The simulator has in its core a discrete event generator creating both mobile (MN-toMN, MN-to-FH) and fixed (FHto-FH) call-related events (such as call setup, call release and call handoff). Calls are characterized by the minimum and maximum QoS value2 , the change (Delta) in the QoS value needed to initiate an update, the average call interarrival time and the average call holding time. Both call arrivals and holding times are exponentially distributed. The parameters associated with each call type are listed in Table 1. The network topology used consists of 9 core nodes, 30 mobile hosts and 3 fixed hosts. The core routers have a forwarding capability of 100Mbps. The average mean degree of connectivity of the core network per node is three. There are two BSs connected to each router. The data rate associated with the wireless link is 10Mbps. The network has a random topology and nodes are randomly positioned over the simulation area. Each MN is associated with a wireless BS and moves to one of the neighboring base stations using a uniform probability. The simulator initiates QoS adaptation procedures upon a call establishment or after a call handoff. 2 We
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Simulation Model
examine only BW adaptation in this work
Figure 3: New Call Blocking Probability for Mobile Calls. The effect of adaptation on the blocking probability for mobile calls is shown in Figure 3. We observe that when mobile calls are allowed to be adaptive, the new call blocking probability is reduced. The improvement is in the order of 14% at high call load. 0.8 Adaptation No Adaptation 0.7
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Figure 4: New Call Blocking Probability for Fixed Calls.
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Dropping Probability
Fixed calls are also blocked at connection time if some part of the network is not able to fulfill their requirements. The improvement when calls are made adaptive is about 28% at high loads (as shown in Figure 4. Compared to mobile calls, the improvement for fixed calls is larger because fixed calls can support higher maximum bandwidth, thus the bandwidth window is larger and the applications are more satisfied. The plots also reveal that the blocking probability of all calls increases with call load. The network setup in the simulator used three fixed hosts. Those hosts were participating in both fixedto-fixed and fixed-to-mobile connections. At high call densities, attempted calls to each fixed host can exceed the link capacity of 100Mbps, resulting in call blocking. This explains the sudden increase in the number of blocked fixed calls, when the total number of generated new calls exceed 11000.
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Figure 6: Handoff Dropping Probability.
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3.2.2.
Contributions to New Call Blocking
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Figure 7: QoS satisfaction probability. 0.2
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Figure 5: Contributors to New Call Blocking
Figure 5 shows which part of the network (wireless or fixed) is more likely to deny the admission of new calls. It is clear from the graph that the base stations are the main contributors to new call blocking (80%), while blocked calls arising from QoS deficiencies over the core routers in the network account for less than 20%. These values remain relatively constant with increasing traffic load.
3.2.4.
In the simulation, QoS satisfaction for mobile calls is defined as the ability to satisfy the “previously-granted QoS”, not the “originally-granted QoS” assigned during a mobile call setup. Figure 7 shows QoS satisfaction probabilities for both of these cases. The graph shows that satisfying the “previously-granted QoS” is more likely to be successful than satisfying the “originallygranted QoS”. The improvement is about 5% for all traffic loads examined. Frequent achievement of QoS satisfaction implies lesser need for QoS adaptation update. This is desirable because it reduces the amount of signaling generated in the network. 3.2.5.
3.2.3.
QoS Satisfaction Probability
QoS Upgrade Probability
Handoff Dropping Probability
Figure 6 shows the handoff dropping probability in the mob-QoS framework when QoS adaptation is employed compared to a framework with no adaptation. In a similar fashion as new call blocking probability, handoff dropping probability increases with increasing admitted calls. With QoS adaptation employed, the handoff dropping probability is reduced by approximately 4% over a wide range of traffic load.
Figure 8 reveals that when the total number of admitted calls is low, the upgrade probability is very low. Since most of the calls could have their maximum requested BW fulfilled at call setup we avoid the need for QoS upgrade. As call density increases, the ability to perform a QoS upgrade increases too because there are more calls with degraded QoS from a previous handoff which can be upgraded. The change in QoS upgrade probability was very large
work is handling a lot of traffic and hence, if a call’s QoS requirement cannot be fulfilled, it is much more likely to be dropped than adapted.
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Figure 8: Mobile QoS Upgrade Probability.
at the beginning, increasing from 3.7% up to 5.2% with just 1000 new admitted calls. Calls continued to be upgraded with the same probability until the total number of admitted calls reached 3200. Thereafter, the upgrade probability shows a gradual decrease. This was attributed to the fact that at high load, the BSs’ channel capacities could be occupied with existing on-going traffic such that an upgrade adaptation for an incoming handoff call was impossible. Another reason is that there is little opportunity to adapt when the wired network links became congested. In the network simulated here, most (98%) of the attempted upgrades failed because of QoS deficiencies over the wireless links. 3.2.6.
QoS Degradation Probability
This paper presented a framework for the adaptation of QoS in a wireless mobile environment (Mob-QoS). This framework can be used to support QoS in mobile wireless networks employing either virtual path setup (such as in MPLS) or path resource reservation (such as in IntServ/RSVP). This framework has the ability to cope with inconsistencies created from mobility events (e.g. handoffs) in an end-to-end fashion. A detailed breakdown of all processes involved in both application and network adaptation was presented; namely, procedures for Satisfying, Degrading and Upgrading MobQoS. The simulation results presented clearly show that the proposed QoS adaptation framework for mobile networks can reduce the new call blocking probability for both mobile and fixed calls by at least 14% and the handoff dropping probability by 4% for a wide rage of traffic loads.
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[4] T-W. Chen, P. Krzyzanowski, M.R. Lyu, C. J. Sreenan and John Trotter. ‘A VC-based API for Renegotiable QoS in Wireless ATM Networks’. In Proceedings of ICUPC’97, 1997.
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[5] J.Liu, J.Lin, W.Shih, A.Yu, J.Chung and Z.Wei. ‘Algorithms For Scheduling Imprecise Computations’. IEEE Computer, 24(5):58–68, May 1991.
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Figure 9: Mobile QoS Degradation Probability.
QoS degradation is expected to be more prevalent as the traffic load increases. However, at a certain level of traffic load, further QoS degradation may not be successful owing to the fact that the degraded QoS is below the minimum acceptable QoS required by the application. This phenomenon is reflected by Figure 9 when the total number of admitted calls reaches 3200. Further increase in offered load thereafter did not result in an increase in degradation probability. At high call densities, the net-
[6] Mischa Schwartz. ‘Network Management and Control Issues in Multi-Media Wireless Networks’. IEEE Personal communications Magazine, 2(3):8– 16, June 1995. [7] Christophe Diot. ‘Adaptive Applications & QoS Guaranties’. In Proceedings of International Conference on Multi-Media Networking, pages 99–106, September 1995. [8] Kam Lee. ‘Adaptive Network Support For Mobile Multi-Media’. In Proceedings of the MobiCom’95 : ACM First International Conference on Mobile Computing & Networking, pages 62–72, November 1995.
